# Introduction In this lab, we will explore the K-Means Clustering algorithm and its implementation in Python using the scikit-learn library. Clustering is a type of unsupervised learning that involves grouping data points into clusters based on their similarities. K-Means Clustering is a popular algorithm for clustering and is widely used in various fields such as image processing, bioinformatics, and marketing research. ## VM Tips After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice. Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook. If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.
Click the virtual machine below to start practicing